Objectives

Previously…

The guiding principle of data science is the data science life cycle.

The Data Science Life Cycle

Project Expectations

Purpose of Project Phases

• Breaks the semester-long project into manageable tasks
• Ensures incremental progress and structured development

Presentation Requirements

• Format: 3-minute presentation with 3 well-designed slides

• Focus Areas:

  1. Tasks: Define objectives, problem, and targeted outcomes
  2. Progress Achieved: Highlight key work completed and challenges addressed
  3. Next Tasks: Outline upcoming steps, hurdles, and contingency plans

Best Practices

• Use visual aids (charts, graphs, images) for clarity
• Keep content concise and focused
• Maintain professional and engaging delivery

Project Milstone vs Phase

Project Phases

• Represent minor stages in a project.
• Each phase involves specific tasks contributing to the overall project.

Project Milestones

• Checkpoints that confirm progress and alignment with objectives.
• Do not involve tasks but indicate completion of a phase or key achievement.

Data Sets (1/10): Survivor

Source: surivoR

Data Sets (2/10): Flights

Source: anyflights

Data Sets (3/10): Census

Source: tidycensus

Data Sets (4/10): Jeopardy

Source: 200,000+ Jeopardy! Questions

Data Sets (5/10): Spotify Songs

Source: Spotify Million Song Dataset (Kaggle)

Data Sets (6/10): Fake News

Source: Fake News detection dataset (Kaggle)

Data Sets (7/10): Spam Emails

Source: E-Mail classification NLP (Kaggle)

Data Sets (8/10): Apps

Source 1: Apple AppStore Apps (Kaggle) Source 2: Google Play Store Apps (Kaggle)

Data Sets (9/10): Movies

Source: IMDb Non-Commercial Datasets

Data Sets (10/10): Twitter

Source: Twitter Hashtag 94 Data

Project Proposal

Frame your data science project, establish objectives, and outline the approach to solving it. Requirements:

• Clearly define the problem or research question.
• Specify the dataset(s) to be used and their relevance.
• Outline the methods or techniques to be employed (e.g., exploratory data analysis, modeling, visualization).

While you think about your proposal, here are key contents that must exist in your overall project:

• Data wrangling of a main data set and multiple secondary related data sets
• Data visualization of common plots and with at least one of each type such as temporal, spatial, and network plots
• (Optional) Mathematical/Statistical modeling and/or inference

Activity: Getting Started with your Project

1. Log-in to Posit Cloud and open the R Studio assignment Project AlexQ.

2. Replace the project name Project AlexQ to your name using the format Project [First name][Last initial].

3. Create a new RMarkdown file and modify it with your name. Remove the default texts.

4. Choose one data set in the given list. In your Rmarkdown file, provide the following information:

   • Define your problem or research question
   • Specify the dataset(s) to be used and their relevance
   • Outline the methods or techniques to be employed

5. When finished, knit your .Rmd to .html, and create a 3-slide presentation that summarizes your report, then Submit your work to Moodle.